199 research outputs found

    Recombinant hepatitis B surface antigen and anionic phospholipids share a binding region in the fifth domain of β2-glycoprotein I (apolipoprotein H)

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    AbstractHuman β2-glycoprotein I (β2GPI) binds to recombinant hepatitis B surface antigen (rHBsAg), but the location of the binding domain on β2GPI is unknown. It has been suggested that the lipid rather than the protein moiety of rHBsAg binds to β2GPI. Since β2GPI binds to anionic phospholipids (PL) through its lipid-binding region in the fifth domain of β2GPI, we predicted that this lipid-binding region may also be involved in binding rHBsAg. In this study, we examined rHBsAg binding to two naturally occurring mutants of β2GPI, Cys306Gly and Trp316Ser, or evolutionarily conserved hydrophobic amino acid sequence, Leu313-Ala314-Phe315 in the fifth domain of β2GPI. The two naturally occurring mutations and two mutagenized amino acids, Leu313Gly or Phe315Ser, disrupted the binding of recombinant β2GPI (rβ2GPI) to both rHBsAg and cardiolipin (CL), an anionic PL. These results suggest that rHBsAg and CL share the same region in the fifth domain of β2GPI. Credence to this conclusion was further provided by competitive ELISA, where CL-bound rβ2GPI was incubated with increasing amounts of rHBsAg. As expected, pre-incubation of rβ2GPI with CL precluded binding to rHBsAg, indicating that CL and rHBsAg bind to the same region on β2GPI. Our data provide evidence that the lipid (PL) rather than the protein moiety of rHBsAg binds to β2GPI and that this binding region is located in the fifth domain of β2GPI, which also binds to anionic PL

    Population-Based Resequencing of LIPG and ZNF202 Genes in Subjects with Extreme HDL Levels

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    Endothelial lipase (LIPG) and zinc finger protein 202 (ZNF202) are two pivotal genes in high density lipoprotein (HDL metabolism). We sought to determine their genetic contribution to variation in HDL-cholesterol levels by comprehensive resequencing of both genes in 235 individuals with high or low HDL-C levels. The selected subjects were 141 Whites (High HDL Group: n = 68, x¯=76.90mg/dl; Low HDL Group: n = 73, x¯=32.55mg/dl) and 94 Hispanics (High HDL Group: n = 46, x¯=74.85mg/dl; Low HDL Group: n = 48, x¯=29.95mg/dl). We identified a total of 185 and 122 sequence variants in LIPG and ZNF202, respectively. We found only two missense variants in LIPG (T111I and N396S) and two in ZNF202 (A154V and K259E). In both genes, there were several variants unique to either the low or high HDL group. For LIPG, the proportion of unique variants differed between the high and low HDL groups in both Whites (p = 0.022) and Hispanics (p = 0.017), but for ZNF202 this difference was observed only in Hispanics (p = 0.021). We also identified a common haplotype in ZNF202 among Whites that was significantly associated with the high HDL group (p = 0.013). These findings provide insights into the genetics of LIPG and ZNF202, and suggest that sequence variants occurring with high frequency in non-exonic regions may play a prominent role in modulating HDL-C levels in the general population

    Population Distributions of APOE, APOH, and APOA4 Polymorphisms and Their Relationships with Quantitative Plasma Lipid Levels among the Evenki Herders of Siberia

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    Island populations are most informative in the study of the genetic structure of human aggregates. These populations are often of small size, thus violating the Hardy-Weinberg assumption of infinite size. Some geographically isolated island populations are further subdivided by religion, ethnicity, and socioeconomic factors, reducing their effective sizes and facilitating genetic changes due to stochastic processes. Because of extreme geographic and social isolation, fishing communities or outports of Newfoundland have been investigated for genetic microdifferentiation through the founder effect and genetic drift (Crawford et al. 1995). The purpose of this paper is to examine the population structure of 10 Newfoundland outports using the allelic frequencies derived from 12 red cell antigens. To achieve this goal, first we calculated gene frequencies using maximum-likelihood estimation procedures. Second, we used R-matrix methods to explore population differentiation. Third, we regressed mean per-locus heterozygosity on genetic distance from the gene frequency centroid to identify the most isolated populations. On the basis of this information, the three outports of Seal Cove, Island Harbor, and Tilting were found to be genetically differentiated from the other small populations. Moreover, religious and geographic subdivisions appear to explain the observed genetic variation

    Dataset of why inclusion matters for Alzheimer's disease biomarker discovery in plasma

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    Here we present a plasma proteomics dataset that was generated to understand the importance of self-reported race for biomarker discovery in Alzheimer's disease. This dataset is related to the article “Why inclusion matters for Alzheimer's disease biomarker discovery in plasma” [1]. Plasma samples were obtained from clinically diagnosed Alzheimer's disease and cognitively normal adults of African American/Black and non-Hispanic White racial and ethnic backgrounds. Plasma was immunodepleted, digested, and isobarically tagged with commercial reagents. Tagged peptides were fractionated using high pH fractionation and resulting fractions analysed by liquid chromatography – mass spectrometry (LC-MS/MS & MS3) analysis on an Orbitrap Fusion Lumos mass spectrometer. The resulting data was processed using Proteome Discoverer to produce a list of identified proteins with corresponding tandem mass tag (TMT) intensity information

    Connecting the dots: Potential of data integration to identify regulatory snps in late-onset alzheimer's disease GWAS findings

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    Late-onset Alzheimer's disease (LOAD) is a multifactorial disorder with over twenty loci associated with disease risk. Given the number of genome-wide significant variants that fall outside of coding regions, it is possible that some of these variants alter some function of gene expression rather than tagging coding variants that alter protein structure and/or function. RegulomeDB is a database that annotates regulatory functions of genetic variants. In this study, we utilized RegulomeDB to investigate potential regulatory functions of lead single nucleotide polymorphisms (SNPs) identified in five genome-wide association studies (GWAS) of risk and age-at onset (AAO) of LOAD, as well as SNPs in LD (r2≥0.80) with the lead GWAS SNPs. Of a total 614 SNPs examined, 394 returned RegulomeDB scores of 1-6. Of those 394 variants, 34 showed strong evidence of regulatory function (RegulomeDB score ,3), and only 3 of them were genome-wide significant SNPs (ZCWPW1/ rs1476679, CLU/rs1532278 and ABCA7/rs3764650). This study further supports the assumption that some of the non-coding GWAS SNPs are true associations rather than tagged associations and demonstrates the application of RegulomeDB to GWAS data.©2014 Rosenthal et al

    PTGER4 expression-modulating polymorphisms in the 5p13.1 region predispose to Crohn's disease and affect NF-κB and XBP1 binding sites.

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    Genome-wide association studies identified a PTGER4 expression-modulating region on chromosome 5p13.1 as Crohn's disease (CD) susceptibility region. The study aim was to test this association in a large cohort of patients with inflammatory bowel disease (IBD) and to elucidate genotypic and phenotypic interactions with other IBD genes. A total of 7073 patients and controls were genotyped: 844 CD and 471 patients with ulcerative colitis and 1488 controls were analyzed for the single nucleotide polymorphisms (SNPs) rs4495224 and rs7720838 on chromosome 5p13.1. The study included two replication cohorts of North American (CD: n = 684; controls: n = 1440) and of German origin (CD: n = 1098; controls: n = 1048). Genotype-phenotype, epistasis and transcription factor binding analyses were performed. In the discovery cohort, an association of rs4495224 (p = 4.10×10⁻⁵; 0.76 [0.67-0.87]) and of rs7720838 (p = 6.91×10⁻⁴; 0.81 [0.71-0.91]) with susceptibility to CD was demonstrated. These associations were confirmed in both replication cohorts. In silico analysis predicted rs4495224 and rs7720838 as essential parts of binding sites for the transcription factors NF-κB and XBP1 with higher binding scores for carriers of the CD risk alleles, providing an explanation of how these SNPs might contribute to increased PTGER4 expression. There was no association of the PTGER4 SNPs with IBD phenotypes. Epistasis detected between 5p13.1 and ATG16L1 for CD susceptibility in the discovery cohort (p = 5.99×10⁻⁷ for rs7720838 and rs2241880) could not be replicated in both replication cohorts arguing against a major role of this gene-gene interaction in the susceptibility to CD. We confirmed 5p13.1 as a major CD susceptibility locus and demonstrate by in silico analysis rs4495224 and rs7720838 as part of binding sites for NF-κB and XBP1. Further functional studies are necessary to confirm the results of our in silico analysis and to analyze if changes in PTGER4 expression modulate CD susceptibility

    Genome-wide association study of brain amyloid deposition as measured by Pittsburgh Compound-B (PiB)-PET imaging

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    Deposition of amyloid plaques in the brain is one of the two main pathological hallmarks of Alzheimer's disease (AD). Amyloid positron emission tomography (PET) is a neuroimaging tool that selectively detects in vivo amyloid deposition in the brain and is a reliable endophenotype for AD that complements cerebrospinal fluid biomarkers with regional information. We measured in vivo amyloid deposition in the brains of ~1000 subjects from three collaborative AD centers and ADNI using 11C-labeled Pittsburgh Compound-B (PiB)-PET imaging followed by meta-analysis of genome-wide association studies, first to our knowledge for PiB-PET, to identify novel genetic loci for this endophenotype. The APOE region showed the most significant association where several SNPs surpassed the genome-wide significant threshold, with APOE*4 being most significant (P-meta = 9.09E-30; β = 0.18). Interestingly, after conditioning on APOE*4, 14 SNPs remained significant at P < 0.05 in the APOE region that were not in linkage disequilibrium with APOE*4. Outside the APOE region, the meta-analysis revealed 15 non-APOE loci with P < 1E-05 on nine chromosomes, with two most significant SNPs on chromosomes 8 (P-meta = 4.87E-07) and 3 (P-meta = 9.69E-07). Functional analyses of these SNPs indicate their potential relevance with AD pathogenesis. Top 15 non-APOE SNPs along with APOE*4 explained 25-35% of the amyloid variance in different datasets, of which 14-17% was explained by APOE*4 alone. In conclusion, we have identified novel signals in APOE and non-APOE regions that affect amyloid deposition in the brain. Our data also highlights the presence of yet to be discovered variants that may be responsible for the unexplained genetic variance of amyloid deposition
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